European Commission Directorate General Economic and Financial Affairs Using BCS data for tracking q-o-q GDP growth Andreas Reuter Business and consumer surveys and short-term forecast (ECFIN A4.2)

2 Outline 2.Relative weaknesses of the Economic Sentiment Indicator (ESI) 4.Improving the ESI's tracking performance of q-o-q GDP growth  step a: re-constructing the ESI based on "best-performing" survey questions  step b: an ESI with amplified changes 3.Refresher on ESI Construction Method 1.Introduction: the Economic Sentiment Indicator (ESI)

3 Added value:  timeliness (complementing delayed quantitative statistics)  high frequency Purpose of the ESI:  summarising developments in all 5 sectors covered by DG ECFIN's Business and Consumer Surveys (BCS):  services  tracking GDP growth at Member State, EU and euro-area level  industry  construction  retail trade  consumers

4 ESI is excellent in tracking GDP growth y-o-y… 2.Relative Weaknesses of the Economic Sentiment Indicator (ESI) Correlations: coincident leading 1 leading 2 However…

5 ESI is less convincing in tracking GDP growth q-o-q… 2.Relative Weaknesses of the Economic Sentiment Indicator (ESI) PMI Correlations: coincident leading 1 leading 2 ESIOECD CLI 2 quarters delay downturn signalled with: 1 quarter delay quickness of recovery underestimated

6 ingredients: balance series of 15 survey questions Effect:  values >100 indicate above-average economic sentiment 3.Refresher on ESI Construction Method The questions are:  seasonally adjusted  standardised allocating weights per sector: Industry: 40% ; Services: 30% ; Consumers: 20% ; Construction: 5% ; Retail Trade: 5% calculation of arithmetic mean of weighted balances standardisation of the ESI and:  addition of 100  multiplication by 10 Effect:  comparability of balance series in terms of mean and volatility  no series dominates development of ESI due to a higher amplitude individual indu question has weight of 13,3% (=40% weight / 3 questions)  2/3 of observations will be in the interval [90 ; 110] (assuming normality) % of positive answers minus % of negative answers

7 4.Improving the ESI's tracking performance of q-o-q GDP growth step a: re-constructing the ESI based on "best-performing" survey questions 1.Correlation of all individual survey questions with i) reference series, ii) q-o-q GDP growth: quarterly averages of balance series for industry: Gross Value Added in Manufacturing for services: Gross Value Added in Services for consumers: Household and NPISH final consumption expenditure for construction: Gross Value Added in Construction for retail trade: Household and NPISH final consumption expenditure

8 2.Construction of 3 new sector-specific Confidence Indicators (CIs):  CIs summarise overall perceptions / expectations at individual sector level 4.Improving the ESI's tracking performance of q-o-q GDP growth – step a: reconstructing the ESI based on "best-performing" survey questions  calculation: arithmetic mean of (seasonally adjusted) balances for specific questions  questions included in sectoral CIs are also the ones used to construct the ESI 1.CI based on the 2 best performing questions (reg. correlation with reference series & GDP q-o-q) 2.CI based on the 3 best performing questions (reg. correlation with reference series & GDP q-o-q) 3.CI based on all forward-looking questions of the respective sector 3.For each sector: selection of the best CI (reg. correlation with reference series & GDP q-o-q)

9 Intermediate Results: 4.Improving the ESI's tracking performance of q-o-q GDP growth – step a: reconstructing the ESI based on "best-performing" survey questions IndustryServicesRetail TradeConsumers order books - currently business - last 3 months business activity (sales) - last 3 months household's fin. position - next 12 months stock of (finished) products - currently demand for firm's services - last 3 months volume of stock - currently econ. situa-tion in MS - next 12 months production - next 3 months demand for firm's services - next 3 months business activity (sales) - next 3 months unemploy-ment in MS - next 12 months likelihood of saving money - next 12 months Construction order books - currently firm's employment - next 3 months production - last 3 months expected level of major purchases - next 12 months expected orders with suppliers - next 3 months building activity - last 3 months 0.61 (0.54)0.65 (0.71)0.46 (0.22)0.64 (0.58) 0.73 (0.68)0.67 (0.73)0.54 (0.27)0.64 (0.69) 0.31 (0.32) 0.32 (0.35) Correlation with GDP q-o-q (with reference series):

10 4.Re-construction of the ESI, using the set of questions of the new CIs: 4.Improving the ESI's tracking performance of q-o-q GDP growth – step a: reconstructing the ESI based on "best-performing" survey questions Slight improvements… Turning points: modified ESI records 0-change in quarter where GDP-downturn starts, while the ESI still signals a rise Amplitude: modified ESI records steeper downward slope than ESI, being more in line with GDP-growth modified ESI % % % Correlations: coincident leading 1 leading 2 ESIimprovement

11 step b: an ESI with amplified changes Intuition of the approach: 4.Improving the ESI's tracking performance of q-o-q GDP growth Comparable changes in the ESI should be taken more "seriously", when reflected by many survey questions. Example: Change in modified ESI: -1.8 Change in modified ESI: -2 Instead: change in ESI should be -2*x (with x > 1) standard deviation of balance series >>>> change in ESI should be multiplied, if a critical amount of questions changes in the same direction We propose: 8 (out of 11) questions We propose: multiplication by 3

12 Calculation of the new method: 4.Improving the ESI's tracking performance of q-o-q GDP growth – step b: an ESI with amplified growth 1.Sum all standardised weighted questions per quarter: 2.Calculate the (modified) ESI: Variable is called: ZNEW

sum of weighted standardised questions (per quarter) 13 4.Improving the ESI's tracking performance of q-o-q GDP growth – step b: an ESI with amplified growth 3.Calculate the absolute change of ZNEW per quarter: 4.Calculate for each quarter a variable taking value 1 if >=8 questions go up / go down : Variable is called: ZNEW change (trigger variable) Variable is called: ZNEW change (amplified) 5.Re-calculate "ZNEW change" mutiplying it by 3 (only in case the "trigger variable" has value 1):

sum of weighted standardised questions (per quarter) 14 4.Improving the ESI's tracking performance of q-o-q GDP growth – step b: an ESI with amplified growth 6.Re-calculate ZNEW, adding "ZNEW change (amplified)" of quarter t to "ZNEW" of quarter t-1: Variable is called: ESINEW (amplified change) Variable is called: ZNEW (amplified) 7.Standardise "ZNEW (amplified)" and thus obtain a new ESI with amplified change:

15 4.Improving the ESI's tracking performance of q-o-q GDP growth – step b: an ESI with amplified growth Results: improvements: compared to current ESI: compared to PMI:  "micro"- volatility of GDP better captured  downturn announced by steeper slope (more in line with GDP)  upswing reflected with steeper slope (in line with GDP)  "micro"- volatility of GDP better captured  better leading properties time-periodcurrent ESIPMIESINEW (ampl.) increase compared to current ESI increase compared to PMI 98Q3 – 02Q10.58 (0.28)0.74 (0.54)0.76 (0.52)31% (85%)4% (-4%) 02Q2 – 07Q10.79 (0.64)0.86 (0.63)0.85 (0.69)8% (8%)-1% (10%) 07Q2 – 12Q20.74 (0.39)0.89 (0.61)0.91 (0.73)23% (87%)2% (18%) 98Q3 – 07Q10.64 (0.41)0.79 (0.58) 25% (41%) 98Q3 – 12Q20.75 (0.49)0.87 (0.65)0.90 (0.73)20% (51%) 0% (0%) 3% (12%) Correlation with GDP growth q-o-q (in brackets: leading 1 correlations)

16 Conclusion :  BCS data can be used to construct indicator tracking q-o-q GDP growth satisfactorily  key of the approach: consider not only the (average) values of the balance series, but also the amount of series moving up/down  approach is still in its infancy and needs further testing

17 4.Improving the ESI's tracking performance of q-o-q GDP growth – step b: an ESI with amplified growth Shortcomings of the approach Is it possible to apply the same construction method to monthly data? Calculations are done with quarterly averages of BCS questions >>>> indicator could only be published once a quarter technically yes ! Will quarterly averages of the resulting monthly ESI-series remain well-correlated with q-o-q GDP growth? yes:  even slightly higher correlations with GDP q-o-q  correlation of the two quarterly ESI series is at 0.97 However…

18 4.Improving the ESI's tracking performance of q-o-q GDP growth – step b: an ESI with amplified growth – Shortcomings of the approach Problem of constructing ESI with amplified changes for monthly data: too high volatility Sep 2009: in upswing-period, ESINEW with amplified changes drops by 10 points (=1 standard deviation)

19 4.Improving the ESI's tracking performance of q-o-q GDP growth – step b: an ESI with amplified growth – Shortcomings of the approach  If amplification is applied in t-1, but not in t, ESI will usually suggest a drop in sentiment in t (also in case the underlying data continues the upward/downward trend of t-1) Source of volatility (note: amplifying changes does not only increase the amplitude of the series, but also its volatility): +2 +2*3 = +6  This additional volatility improves the fit of our quarterly series, but renders the monthly series TOO volatile.  Main reason for this difference: criterion for amplification is more restrictive in case of quarterly set-up:  for quarterly: >= 8 questions must have gone up/down over 3 months-period (amplification in 63% of quarters)  for monthly: >= 8 questions must have gone up just one month (amplification in 73% of the months)

20 4.Improving the ESI's tracking performance of q-o-q GDP growth – step b: an ESI with amplified growth – Shortcomings of the approach Solution :  When multiplying change of t (compared to t-1), the resulting amplified change should be added to ESI for month t, but also ESI of t+1 and t+2 (1/3 of the change respectively should be added). Approach smoothens the monthly curve substantially… When constructing quarterly averages, correlations with q-o-q GDP growth remain high.